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Update Monte_Carlo.py #8

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68a2c66
Update Monte_Carlo.py
noamgariani11 Oct 1, 2024
b9c887e
Update Monte_Carlo.py
noamgariani11 Oct 1, 2024
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4 changes: 2 additions & 2 deletions Solvers/Monte_Carlo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,7 @@ def make_epsilon_greedy_policy(self):
Use:
self.Q: A dictionary that maps from state -> action-values.
Each value is a numpy array of length nA
self.options.epsilon: Chance the sample a random action. Float betwen 0 and 1.
self.options.epsilon: Chance the sample a random action. Float between 0 and 1.
self.env.action_space.n: Number of actions in the environment.

Returns:
Expand Down Expand Up @@ -146,7 +146,7 @@ def train_episode(self):
Run a single episode of Monte Carlo Control Off-Policy Control using Weighted Importance Sampling.

Use:
elf.env: OpenAI environment.
self.env: OpenAI environment.
self.options.steps: steps per episode
self.behavior_policy(state): returns a soft policy which is the
behavior policy (act according to this policy)
Expand Down